JP7236768B2 - Calculation method of coronary flow reserve ratio based on myocardial blood flow and CT image - Google Patents
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Description
本発明は冠状動脈画像学評価分野に関し、特に心筋血流量及びCT画像に基づく冠状動脈冠血流予備量比の計算方法に関する。 The present invention relates to the field of coronary artery imaging assessment, and more particularly to a method for calculating coronary flow reserve ratio based on myocardial blood flow and CT images.
冠状動脈造影及び血管内超音波はいずれも冠動脈性心疾患を診断する“ゴールデンスタンダード”として考えられているが、これらは病変狭窄程度に対して画像学評価できるだけであり、狭窄が遠位血流に対して果たしてどれほど大きな影響を及ぼすかについては知ることができない。冠血流予備量比(FFR)は現在既に冠動脈狭窄機能性評価の公認指標となっており、その最も重要な機能は一つの影響が知られていない冠動脈狭窄の機能結果に対して正確な評価を行うことである。 Both coronary angiography and intravascular ultrasound are considered “golden standards” for diagnosing coronary heart disease. I don't know how big an impact it will have. Fractional coronary flow reserve (FFR) has already become an official index for assessing coronary artery stenosis functionality, and its most important function is to accurately assess the functional consequences of coronary artery stenosis, whose effects are unknown. is to do
冠血流予備量比(FFR)は冠状動脈に狭窄病変が存在する場合において、目標測定血管が心筋領域のために得られる最大血流量と同一領域の理論上の正常下で得られる最大血流量の比を指す。FFR主に冠状動脈狭窄遠位圧力と大動脈根部圧力の比を計算することにより得る。狭窄遠位圧力は圧力ガイドワイヤにより最大灌流血流(パパベリン又はアデノシン又はATPを冠動脈内又は静脈内に注射する)時に測定して得られる。心筋最大充血状態における狭窄遠位冠状動脈内平均圧(Pd)と冠状動脈口部大動脈平均圧(Pa)の比、即ちFFR=Pd/Paと簡略化できる。 Coronary flow reserve ratio (FFR) is the theoretical maximum blood flow obtained in the same region as the maximum blood flow obtained for the myocardial region of the target measurement vessel when there is a stenotic lesion in the coronary artery. refers to the ratio of FFR is primarily obtained by calculating the ratio of distal coronary stenosis pressure to aortic root pressure. Distal stenotic pressure is obtained by pressure guidewire measurement at maximal perfusion blood flow (intracoronary or intravenous injection of papaverine or adenosine or ATP). It can be simplified as the ratio of the stenotic distal intracoronary mean pressure (P d ) to the coronary ostial aortic mean pressure (P a ) at maximal myocardial hyperemia, ie, FFR=P d /P a .
冠動脈CTAは冠動脈狭窄程度を正確に評価でき、且つ血管壁プラーク性質を見分けることができる、一つの非侵襲的で、操作が簡単な冠状動脈病変診断検査方法であり、リスクの高い人をスクリーニングする優先的な方法となる。よって、冠動脈性心疾患患者の血管に対して介入する場合、初期段階で患者冠動脈に対してCTA評価を行わなければならない。 Coronary artery CTA is a non-invasive, easy-to-operate coronary artery lesion diagnostic examination method that can accurately evaluate the degree of coronary artery stenosis and distinguish the characteristics of blood vessel wall plaque, and screen high-risk individuals. be the preferred method. Therefore, when intervening in a patient with coronary heart disease, CTA evaluation must be performed on the patient's coronary artery at an early stage.
冠動脈CTAにより非侵襲で得られたFFR(CTFFR)を計算する場合、別途、イメージング検査又は薬は不要であり、根本的に、不必要な冠動脈血管造影と血行再建治療を避けることができる。DeFacto試験結果でも明確に表明されているように、冠状動脈CTにおいて、CTFFR結果の分析は本当の血流が制限され、病人のリスクが増加する病変の生理情報を提供する。CTFFRは冠動脈CTAとFFRの優位性を組み合わせ、構造及び機能の両面から冠状動脈狭窄を評価することができ、冠動脈病変解剖学及び機能学情報の新規の非侵襲性検出体系を提供するものとなる。しかしCTAは充血状態における冠動脈流速を測定できず、数値方法に頼って予測するしかないため、CTFFRの臨床応用を大いに制限している。 When calculating the FFR obtained non-invasively by coronary CTA (CTFFR), no additional imaging tests or drugs are required, essentially avoiding unnecessary coronary angiography and revascularization treatment. As clearly demonstrated in the DeFacto study results, in coronary CT, analysis of CTFFR results provides physiologic information of true blood flow-limiting lesions that increase patient risk. CTFFR combines the advantages of coronary CTA and FFR to assess coronary artery stenosis both structurally and functionally, providing a novel non-invasive detection system for coronary lesion anatomic and functional information. . However, CTA cannot measure the coronary artery flow velocity in hyperemic conditions and can only be predicted by relying on numerical methods, which greatly limits the clinical application of CTFFR.
上記技術課題を解決するために、本発明は、非侵襲的測定により安静状態心筋血流量及び冠状動脈冠血流予備能(CFR)を特定し、そして冠動脈ツリーにおける異なる血管内面の最大充血状態の流量を特定し、そして最大充血状態の流速V1を特定することによって、冠血流予備量比FFRを早く、正確に、全自動で得ることができる、心筋血流量及びCT画像に基づく冠状動脈冠血流予備量比の計算方法を提供することを目的とする。 In order to solve the above technical problems, the present invention identifies resting-state myocardial blood flow and coronary flow reserve (CFR) by non-invasive measurement, and measures the maximal hyperemia of different vessel linings in the coronary artery tree. By specifying the flow rate and specifying the maximum hyperemic flow velocity V 1 , the coronary flow reserve ratio FFR can be obtained quickly, accurately, and fully automatically. It is an object of the present invention to provide a method for calculating coronary flow reserve ratio.
本発明の技術方案は以下のとおり:
心筋血流量及びCT画像に基づく冠状動脈冠血流予備量比の計算方法は以下のステップを含む:
S01:心臓CT画像を分割し、形態学操作により心臓画像を得て、当該心臓画像をヒストグラム分析して心室心房画像を得て、心臓画像と心室心房画像の差分により心筋画像を得て、心筋画像に基づいて心筋体積を特定し、
S02:大動脈画像を処理して全大動脈相補画像を得て、領域成長を行い、冠状動脈口を含む大動脈画像を得て、冠状動脈口を含む大動脈画像と全大動脈相補画像に基づき、冠状動脈口を含む画像を得て、冠状動脈口を含む画像に基づいて冠状動脈口を特定し、
S03:心筋画像において冠状動脈口をシードポイントとし、領域成長により冠状動脈を抽出し、冠状動脈の平均グレースケール及び平均分散を計算し、冠動脈グレースケール分布に基づき、冠状動脈方向に沿って冠動脈ツリーを抽出し、
S04:冠状動脈画像を二値化し、等値面画像を描き、冠状動脈三次元格子画像を得て、
S05:最大充血状態における冠動脈入口箇所の総流量Qtotal=心筋体積×心筋血流量×CFRを計算し、CFRは冠状動脈冠血流予備能(coronary flow reserve:CFR)であり、
S06:充血状態における血流速度V1を計算し、
S07:V1を冠動脈狭窄血管の入口流速とし、冠動脈入口から冠動脈狭窄遠位までの圧力損失ΔP、狭窄遠位冠状動脈内平均圧Pd=Pa-ΔPを計算し、但し、Paは大動脈平均圧であり、冠血流予備量比FFR=Pd/Paを得る。
The technical solution of the present invention is as follows:
A method for calculating coronary coronary flow reserve ratio based on myocardial blood flow and CT images includes the following steps:
S01: Divide a cardiac CT image, obtain a cardiac image by morphological manipulation, histogram-analyze the cardiac image to obtain a ventricular-atrial image, obtain a myocardial image by difference between the cardiac image and the ventricular-atrial image, and obtain a myocardial image. identify the myocardial volume based on the image;
S02: Processing the aorta image to obtain a total aorta complementary image, performing region growing to obtain an aorta image including the coronary ostia, and based on the aorta image including the coronary ostia and the total aorta complementary image, the coronary ostia obtaining an image containing the ostium of the coronary artery, identifying the ostium of the coronary artery based on the image containing the ostium of the coronary artery;
S03: Using the coronary artery ostium as a seed point in the myocardial image, extracting the coronary artery by region growing, calculating the mean grayscale and mean variance of the coronary artery, and constructing the coronary artery tree along the coronary artery direction based on the coronary artery grayscale distribution. and extract
S04: Binarize the coronary artery image, draw an isosurface image, obtain a three-dimensional grid image of the coronary artery,
S05: Calculate the total flow Q total at the coronary artery ostium in the state of maximal hyperemia = myocardial volume × myocardial blood flow × CFR, where CFR is the coronary flow reserve (CFR);
S06: Calculate the blood flow velocity V1 in the congested state,
S07: Let V1 be the inlet flow velocity of the coronary artery stenosis, calculate the pressure loss ΔP from the coronary artery inlet to the distal coronary artery stenosis, and the mean intracoronary artery pressure distal to the stenosis P d = P a - ΔP, where P a is the aorta is the mean pressure, yielding the coronary flow reserve ratio FFR=P d /P a .
好ましい技術方案において、前記ステップS02において、冠状動脈口を含む画像を得た後、冠状動脈口を含む画像に対して連結領域分析を行い、異なるグレースケールラベルで各連結領域をマークし、冠状動脈口を特定する。 In the preferred technical solution, in step S02, after obtaining the image containing the ostia of the coronary arteries, perform connected region analysis on the image containing the ostia of the coronary arteries, mark each connected region with a different grayscale label, and identify the coronary artery Identify mouth.
好ましい技術方案において、前記ステップS02において、心臓画像において、大動脈断面が円状になる特徴を利用し、上行大動脈及び中心線を抽出し、大動脈画像を得る。 In the preferred technical solution, in the above step S02, the ascending aorta and the central line are extracted by using the characteristic that the cross section of the aorta is circular in the heart image to obtain the aorta image.
好ましい技術方案において、前記ステップS04において冠状動脈画像二値化は、冠状動脈画像V1中のボクセルをトラバーサルし、もしボクセル画素が0に等しい場合、当該画素値は変わらず、もし0に等しくない場合、画素値を1とし、一つの新しいデータV2を得ることを含む。 In the preferred technical solution, the coronary artery image binarization in step S04 traverses voxels in the coronary artery image V1, if a voxel pixel is equal to 0, the pixel value remains unchanged; , set the pixel value to 1 and obtain one new data V2.
好ましい技術方案において、前記ステップS05において心筋コントラストエコー法(MCE)または単一光子放射断層撮影法(SPECT)または陽電子放出断層撮影法(PET)または心臓核磁気共鳴画像法(MRI)またはCT灌流により、安静状態心筋血流量及び冠状動脈冠血流予備能(CFR)を特定する。 In a preferred technical solution, in step S05, by myocardial contrast echocardiography (MCE) or single photon emission tomography (SPECT) or positron emission tomography (PET) or cardiac nuclear magnetic resonance imaging (MRI) or CT perfusion , resting-state myocardial blood flow and coronary flow reserve (CFR).
好ましい技術方案において、前記ステップS06は、
S61:流量体積スケーリング則及び心臓CT三次元再構成の心臓表面冠状動脈ツリーに基づき、ツリー内の任意の一本の血管内の血流量Q=Qtotal×(V/Vtotal)3/4を特定し、但し、Vtotalは心臓CT三次元再構成のすべての心臓表面冠状動脈の血管体積の和であり、Vは心臓表面冠状動脈ツリー内の任意の一本の血管及びその下流血管中の血管体積の和であり、
S62:流量体積スケーリング則及び心臓CT三次元再構成の心臓表面冠状動脈ツリーに基づき、ツリー内の任意の一本の血管内の血流速度V1=Q/Dを特定し、但し、Dは当該血管の平均断面積である、ことを含む。
In the preferred technical solution, the step S06 includes:
S61: Based on the flow-volume scaling law and the cardiac surface coronary artery tree of cardiac CT three-dimensional reconstruction, the blood flow in any one vessel in the tree Q = Q total × (V/V total ) 3/4 where V total is the sum of vessel volumes of all superficial coronary arteries in the cardiac CT three-dimensional reconstruction, and V is the volume of any one vessel in the superficial coronary artery tree and its downstream vessels is the sum of vessel volumes ,
S62: Based on the flow-volume scaling law and the cardiac surface coronary artery tree of cardiac CT three-dimensional reconstruction, identify the blood flow velocity V1=Q/D in any one vessel in the tree, where D is the is the average cross-sectional area of blood vessels.
好ましい技術方案において、前記ステップS07は具体的に、
血管三次元格子に対して解を求め、数値解法を用いて連続性及びナビエ-ストークス(Navier-Stokes)方程式の解を求め:
P、ρ、μはそれぞれ流速、圧力、血液密度、血液粘度であり、
入口境界条件は、最大充血状態における冠動脈狭窄血管の入口流速V1であり、
三次元計算流体力学により各冠動脈狭窄の圧力損失ΔP1、ΔP2、ΔP3・・・、冠動脈入口から冠動脈狭窄遠位までの圧力損失ΔP=ΣΔPi(i=1、2、3・・・)、狭窄遠位冠状動脈内平均圧Pd=Pa-ΔPを計算する、但し、Paは大動脈平均であることを含む。
In the preferred technical solution, the step S07 is specifically:
Solve for the vessel 3D grid and solve the continuity and Navier-Stokes equations using numerical methods:
P, ρ, μ are flow velocity, pressure, blood density, blood viscosity, respectively,
The inlet boundary condition is the inlet flow velocity V1 of the coronary artery stenosis at maximum hyperemia,
By three-dimensional computational fluid dynamics, the pressure losses ΔP 1 , ΔP 2 , ΔP 3 , . ), calculate the mean stenotic distal coronary pressure P d =P a -ΔP, where P a is the aortic mean.
好ましい技術方案において、前記ステップS07は、
CT再構成のジオメトリ構造に基づき、狭窄のある血管を真っすぐに引き伸ばし、二次元軸対称モデルを構築し、二次元格子を分割し、数値解法を用いて連続性及びナビエ-ストークス方程式の解を求め:
入口境界条件は、最大充血状態における冠動脈狭窄血管の入口流速V1であり、
二次元流体力学により各冠動脈狭窄の圧力損失ΔP1、ΔP2、ΔP3・・・、冠動脈入口から冠動脈狭窄遠位までの圧力損失ΔP=ΣΔPi(i=1、2、3・・・)、狭窄遠位冠状動脈内平均圧Pd=Pa-ΔPを計算する、但し、Paは大動脈平均圧である、ことを含む。
In the preferred technical solution, the step S07 includes:
Straighten stenosed vessels, build a two-dimensional axisymmetric model, divide the two-dimensional grid, and solve the continuity and Navier-Stokes equations using numerical methods based on the geometric structure of the CT reconstruction. :
The inlet boundary condition is the inlet flow velocity V1 of the coronary artery stenosis at maximum hyperemia,
Pressure loss ΔP 1 , ΔP 2 , ΔP 3 , ΔP 1 , ΔP 2 , ΔP 3 , . , to calculate the stenotic distal intracoronary mean pressure P d =P a -ΔP, where P a is the aortic mean pressure.
好ましい技術方案において、前記ステップS07はさらに、血管の異なるタイプの弯曲に対して、三次元モデルで入口から出口までの圧力差を計算し、二次元軸対称モデルに照らして計算し、各類型の弯曲の二次元軸対称結果に対する修正係数を記憶するためのデータベースを構築し、圧力を得た後、データベース中の修正係数に照らし、修正後の入口から出口までの圧力差を得て、その後FFRを計算する、ことを含む。 In the preferred technical solution, the step S07 further includes calculating the pressure difference from the inlet to the outlet in the three-dimensional model for different types of curvature of the blood vessel, calculating it in the light of the two-dimensional axisymmetric model, and calculating each type of curvature. Build a database for storing correction factors for the two-dimensional axisymmetric result of the curve, obtain the pressure, then look up the correction factors in the database to obtain the corrected inlet-to-exit pressure difference, and then FFR including computing
本発明は心筋血流量及び心臓CT画像により、冠血流予備量比FFRを早く、正確に、全自動で得ることができ、従来のCTFFR(またはFFRCT)の精度を大幅に高めることができる。非侵襲的測定により、操作が簡単で、手術の難度及びリスクを大幅に低減し、臨床で大規模に応用を進めることができる。 The present invention can obtain the coronary flow reserve ratio FFR quickly, accurately, and fully automatically from the myocardial blood flow and cardiac CT images, and can greatly improve the accuracy of the conventional CTFFR (or FFRCT). Non-invasive measurement is easy to operate, greatly reduces the difficulty and risk of surgery, and can be applied clinically on a large scale.
以下に図面及び実施例と合わせて本発明を更に説明する。 The present invention will be further described in conjunction with the drawings and examples below.
本発明の目的、技術方案及び長所をより明確に説明するために、以下に図面を参照しながら発明を実施するための形態と合わせて、本発明について、さらに詳細に説明する。これら説明は単なる例であり、本発明の範囲を限定するものではないと理解されるべきである。この他、以下の説明において、本発明の概念と不要な混同を避けるために、公知の構造及び技術に関する説明は省略する。 In order to more clearly describe the purpose, technical solution and advantages of the present invention, the present invention will be described in more detail below together with the detailed description of the invention with reference to the accompanying drawings. It should be understood that these descriptions are examples only and do not limit the scope of the invention. In addition, in the following description, descriptions of known structures and techniques are omitted to avoid unnecessary confusion with the concepts of the present invention.
所定の心臓CT画像について、リバースメソッドにより、心臓を抽出し、非目標領域である下行大動脈、脊椎、肋骨を対象に処理を行い、一つ一つ胸壁、肺部、椎骨及び下行大動脈等の非心臓組織を取り除いて心臓画像を抽出して得る。得られた心臓画像において、大動脈断面が円状になる特徴を利用し、上行大動脈及び中心線を抽出し、大動脈画像を得る。 For a predetermined cardiac CT image, the heart is extracted by the reverse method, and the non-target areas such as the descending aorta, spine, and ribs are processed, and non-target areas such as the chest wall, lungs, vertebrae, and descending aorta are extracted one by one. A heart image is obtained by removing the heart tissue. In the obtained cardiac image, the ascending aorta and the central line are extracted using the feature that the cross section of the aorta is circular to obtain the aorta image.
図1に示されるように、本発明の心筋血流量及びCT画像に基づく冠状動脈冠血流予備量比(FFR)の計算方法は、心筋画像を抽出し、冠状動脈口を抽出し、冠状動脈を抽出し、冠状動脈格子モデルを生成し、安静状態心筋血流量及び冠状動脈冠血流予備能(CFR)を特定し、最大充血状態における冠動脈入口箇所の総流量を計算し、充血状態における血流速度V1を計算し、冠状動脈FFRを特定することを含む。具体的に以下のステップを含む: As shown in FIG. 1, the calculation method of the coronary artery flow reserve ratio (FFR) based on the myocardial blood flow and CT image of the present invention extracts the myocardial image, extracts the coronary ostium, and extracts the coronary artery to generate a coronary artery grid model, determine the resting-state myocardial flow and the coronary flow reserve (CFR), calculate the total flow at the coronary ostium at maximal hyperemia, Calculating the flow velocity V 1 and identifying the coronary artery FFR. It specifically includes the following steps:
1:心筋画像を抽出する:
心臓CT画像を分割し、形態学操作により心臓画像を得て、当該心臓画像をヒストグラム分析して心室心房画像を得て、心臓画像と心室心房画像の差分により心筋画像を得る。図2参照。
1: Extract myocardial images:
A cardiac CT image is segmented, a cardiac image is obtained by morphological manipulation, the cardiac image is histogram-analyzed to obtain a ventricular-atrial image, and a difference between the cardiac image and the ventricular-atrial image is obtained to obtain a myocardial image. See Figure 2.
2:冠状動脈口を抽出する:
大動脈画像の二値化画像に対して形態学膨張を行い、全大動脈の二値画像を得て、そして画素リバースにより全大動脈相補画像を得る。
大動脈中心線上点の平均グレースケールに基づき領域成長を行い、冠状動脈口を含む大動脈画像を得る。図3参照。
冠状動脈口を含む大動脈画像と全大動脈相補画像により画像乗算を行い、冠状動脈口を含む画像を得て、冠状動脈口を含む画像に対して連結領域分析を行い、異なるグレースケールラベルで各連結領域をマークし、冠状動脈口を特定する。図4参照。
2: Extract the coronary ostia:
Morphological dilation is performed on the binarized image of the aorta to obtain a binary image of the whole aorta, and pixel reversal to obtain a complemented whole aorta image.
Region growing is performed based on the mean grayscale of points on the aortic centerline to obtain an aortic image that includes the coronary ostia. See FIG.
Perform image multiplication by the aorta image including the coronary ostia and the total aorta complementary image to obtain the image including the coronary ostia, perform connected region analysis on the image including the coronary ostia, and label each connection with a different grayscale label. Mark the area and identify the coronary ostia. See FIG.
3:冠状動脈を抽出する:
心筋画像において冠状動脈口をシードポイントとし、領域成長により冠状動脈を抽出し、冠状動脈の平均グレースケール及び平均分散を計算し、冠動脈グレースケール分布に基づき、冠状動脈方向に沿って冠動脈ツリーを抽出する。図5参照。
3: Extract the coronary arteries:
Using the coronary artery ostia as seed points in the myocardial image, extracting the coronary arteries by region growing, calculating the mean grayscale and mean variance of the coronary arteries, and extracting the coronary artery tree along the coronary artery direction based on the coronary artery grayscale distribution. do. See FIG.
4:冠状動脈格子モデルを生成する:
ステップ三により、冠状動脈画像データV1を得て、当該データ中のボクセルは空間上に一つの立方体を構成し、冠状動脈部分に属すボクセル画素値は0ではなく(画素値約-3000~3000の間)、残りのボクセル画素値はすべて0である。
本ステップにおいて、ステップ五におけるFFR計算のために、データを空間三次元格子データV3に変える必要がある。
4: Generate a coronary artery grid model:
In step 3, the coronary artery image data V1 is obtained, the voxels in the data constitute one cube in space, and the voxel pixel values belonging to the coronary artery are not 0 (pixel values of about -3000 to 3000). between), the remaining voxel pixel values are all zero.
In this step, it is necessary to transform the data into spatial three-dimensional grid data V3 for the FFR calculation in step 5.
(1)冠状動脈データ二値化
冠状動脈画像データV1中のボクセルをトラバーサルし、簡単な画素値判断を行い、もし画素A1が0に等しい場合、当該画素値は変わらず、もしA1が0に等しくない場合、A1の画素値を1とする。
最終的に一つの新しい画像データV2が得られ、当該画像において、冠状動脈部分に属するボクセル画素値は1であり、残りの部分は0である。
(1) Coronary artery data binarization Traversal the voxels in the coronary artery image data V1 and perform a simple pixel value judgment, if pixel A1 is equal to 0, the pixel value is unchanged; If not, let the pixel value of A1 be 1.
Finally, one new image data V2 is obtained, in which the voxel pixel value belonging to the coronary artery portion is 1 and the rest is 0.
(2)等値面生成
ボクセルは一つの極小の六面体であると定義され、隣接する上下層の間の四つの画素が立方体上の八つの頂点を構成する。等値面とは空間中のある同じ属性値を有するすべての点の集合である。これは次のように表すことができる:
{(x、y、z)│f(x、y、z)=c}、cは定数である
本方法におけるcは三次元再構成過程において与えられた画素値1である。
(2) Isosurface generation A voxel is defined as a minimal hexahedron, and four pixels between adjacent layers form eight vertices on the cube. An isosurface is the set of all points in space that have the same attribute value. This can be expressed as:
{(x,y,z)|f(x,y,z)=c}, where c is a constant c in this method is the pixel value 1 given in the 3D reconstruction process.
等値面を抽出するフローは以下のとおり:
(1)原始データを前処理した後、特定の配列に読み込む。
(2)格子データボディから一つのユニットボディを抽出して現在のユニットボディとすると同時に当該ユニットボディのすべての情報を得る。
(3)現在のユニットボディの8個の頂点の函数値と所定の等値面値Cを比較し、当該ユニットボディの状態表を得る。
(4)現在のユニットボディの状態表インデックスから、等値面と交わるユニットボディエッジを探し出し、そして線形補間の方法により各交点の位置座標を計算する。
(5)中心差分法により現在のユニットボディの8個の頂点の法線ベクトルを求め、それから線形補間の方法により三角パッチの各頂点の法線を得る。
(6)各三角パッチの頂点座標及び頂点の法線ベクトルに基づき等値面イメージの作成を行う。
最終的に冠状動脈の三次元格子画像データV3を得る。図6参照。
The flow for extracting isosurfaces is as follows:
(1) After preprocessing the raw data, it is read into a specific array.
(2) Extracting one unit body from the lattice data body to make it the current unit body, and simultaneously obtaining all the information of the unit body.
(3) Compare the function values of the eight vertices of the current unit body with the predetermined isosurface value C to obtain the state table of the unit body.
(4) From the state table index of the current unit body, find the unit body edge that intersects the isosurface, and calculate the position coordinates of each intersection by the method of linear interpolation.
(5) Find the normal vectors of the eight vertices of the current unit body by the central difference method, then obtain the normal of each vertex of the triangular patch by the method of linear interpolation.
(6) An isosurface image is created based on the vertex coordinates and vertex normal vectors of each triangular patch.
Finally, three-dimensional lattice image data V3 of the coronary arteries are obtained. See FIG.
5:充血状態における血流速度V1を計算する:
心筋コントラストエコー法(MCE)または単一光子放射断層撮影法(SPECT)または陽電子放出断層撮影法(PET)または心臓核磁気共鳴画像法(MRI)またはCT灌流等非侵襲的測定により、安静状態心筋血流量及び冠状動脈冠血流予備能(CFR)を特定し、心筋体積、心筋血流量、CFRにより、最大充血状態における冠動脈入口箇所(左冠動脈ツリー及び右冠動脈ツリーの和を含む)の総流量Qtotal=心筋体積×心筋血流量×CFRを計算する。
5: Calculate the blood flow velocity V 1 in the hyperemic state:
Resting-state myocardium by non-invasive measurements such as myocardial contrast echocardiography (MCE) or single photon emission tomography (SPECT) or positron emission tomography (PET) or magnetic resonance imaging (MRI) or CT perfusion Blood flow and coronary coronary flow reserve (CFR) are determined, and myocardial volume, myocardial blood flow, and CFR are the total flow of the coronary ostium (including the sum of the left and right coronary trees) at maximal hyperemia. Calculate Q total = myocardial volume x myocardial blood flow x CFR.
流量体積スケーリング則及び心臓CT三次元再構成の心臓表面冠状動脈ツリーに基づき、ツリー内の任意の一本の血管内の血流量Q:Q=Qtotal×(V/Vtotal)3/4を特定し、但し、Vtotalは心臓CT三次元再構成のすべての心臓表面冠状動脈(左冠動脈ツリー及び右冠動脈ツリーの和を含む)の血管体積の和であり、Vは心臓表面冠状動脈ツリー内の任意の一本の血管及びその下流血管中の血管体積の和である。図7参照。流量体積スケーリング則及び心臓CT三次元再構成の心臓表面冠状動脈ツリーに基づき、特定ツリー内の任意の一本の血管内の血流速度V1:V1=Q/D、但し、Dは当該血管の平均断面積である(当該血管の血管体積を当該血管の長さで割る)。 Based on the flow-volume scaling law and the cardiac surface coronary artery tree of cardiac CT three-dimensional reconstruction, the blood flow Q in any one vessel in the tree: Q = Q total × (V/V total ) 3/4 where V total is the sum of the vascular volumes of all superficial coronary arteries (including the sum of the left and right coronary trees) in the cardiac CT three-dimensional reconstruction, and V is is the sum of vessel volumes in any one vessel of and its downstream vessels. See FIG. Based on the flow volume scaling law and the cardiac surface coronary artery tree of cardiac CT three-dimensional reconstruction, the blood flow velocity in any one vessel in a particular tree V 1 : V 1 =Q/D, where D is the It is the mean cross-sectional area of a vessel (the vessel's vascular volume divided by the vessel's length).
6:冠状動脈FFRの計算:
V1を冠動脈狭窄血管の入り口流速とし、計算流体力学(CFD)方法により各冠動脈狭窄の厚力損失ΔP1、ΔP2、ΔP3等、冠動脈入口から冠動脈狭窄遠位までの圧力損失ΔP=ΣΔPi(i=1、2、3・・・)、狭窄遠位冠状動脈内平均圧Pd=Pa-ΔPを計算し、但し、Paは大動脈平均圧であり、最後に式FFR=Pd/Paにより冠血流予備量比を計算する。
6: Calculation of coronary artery FFR:
Letting V 1 be the flow velocity at the entrance of the coronary artery stenosis, the thickness loss ΔP 1 , ΔP 2 , ΔP 3 etc. of each coronary artery stenosis is calculated by computational fluid dynamics (CFD) method, and the pressure loss ΔP from the coronary artery entrance to the distal coronary artery stenosis ΔP = ΣΔP i ( i = 1, 2, 3...), calculate the mean pressure in the distal stenotic coronary artery P d = P a - ΔP, where P a is the mean aortic pressure, and finally the formula FFR = P Calculate the coronary flow reserve ratio as d / Pa .
三次元モデルに対する処理ステップは以下を含む:
CT再構成のジオメトリ構造に基づき、三次元格子を分割し、数値解法(例えば、有限差分、有限要素法、有限体積法等)により連続性及びナビエ-ストークス(Navier-Stokes)方程式の解を求め:
P、ρ、μはそれぞれ流速、圧力、血液密度、血液粘度であり、
入口境界条件は、最大充血状態における冠動脈狭窄血管の入口流速V1であり、
式[A1]及び[A2]に基づき、三次元CFDを実行して各冠動脈狭窄の圧力損失ΔP1、ΔP2、ΔP3等、冠動脈入口から冠動脈狭窄遠位までの圧力損失ΔP=ΣΔPi(i=1、2、3・・・)、狭窄遠位冠状動脈内平均圧Pd=Pa-ΔPを計算し、但し、Paは大動脈平均圧である。
Processing steps for 3D models include:
Based on the geometrical structure of the CT reconstruction, the 3D grid is partitioned and the continuity and Navier-Stokes equations are solved by numerical methods (e.g., finite difference, finite element method, finite volume method, etc.). :
P, ρ, μ are flow velocity, pressure, blood density, blood viscosity, respectively,
The inlet boundary condition is the inlet flow velocity V1 of the coronary artery stenosis at maximum hyperemia,
Based on equations [A1] and [A2], three-dimensional CFD was performed to determine the pressure drop ΔP 1 , ΔP 2 , ΔP 3 , etc. of each coronary artery stenosis, and the pressure loss ΔP from the coronary ostium to the distal coronary artery stenosis ΔP = ΣΔP i ( i = 1, 2, 3...), calculate the stenotic distal intracoronary mean pressure P d = P a -ΔP, where P a is the aortic mean pressure.
二次元モデルに対して、以下のステップを含む:
CT再構成のジオメトリ構造に基づき、狭窄のある血管を真っすぐに引き伸ばし(二次元軸対称モデル)、二次元格子を分割し、数値解法(例えば、有限差分、有限要素法、有限体積法等)により連続性及びナビエ-ストークス方程式の解を求め:
入口境界条件は、最大充血状態における冠動脈狭窄血管の入口流速V1であり、
式[A3]~[A5]に基づき、二次元CFDを実行し、各冠動脈狭窄の圧力損失ΔP1、ΔP2、ΔP3等、冠動脈入口から冠動脈狭窄遠位までの圧力損失ΔP=ΣΔPi(i=1、2、3・・・)、狭窄遠位冠状動脈内平均圧Pd=Pa-ΔPを計算し、但し、Paは大動脈平均圧である。
For 2D models, it includes the following steps:
Based on the geometric structure of the CT reconstruction, straighten the stenosed vessels (2D axisymmetric model), divide the 2D grid, and use numerical methods (e.g., finite difference, finite element method, finite volume method, etc.) Find continuity and solutions to the Navier-Stokes equation:
The inlet boundary condition is the inlet flow velocity V1 of the coronary artery stenosis at maximum hyperemia,
Based on the equations [A3] to [A5], two-dimensional CFD is performed and the pressure loss ΔP 1 , ΔP 2 , ΔP 3 etc. of each coronary artery stenosis, and the pressure loss ΔP from the coronary ostium to the distal coronary artery stenosis ΔP = ΣΔP i ( i = 1 , 2 , 3, .
血管の異なるタイプの弯曲に対して、三次元モデルで入口から出口までの圧力差を計算し、二次元軸対称モデルに照らして計算し、各類型の弯曲の二次元軸対称結果に対する修正係数を記憶するためのデータベースを構築し、圧力算出後データベース中の修正係数に照らし、修正後の入口から出口までの圧力差を得て、最後に式により計算FFRを計算する。 For different types of curvature of the vessel, the pressure difference from the inlet to the outlet is calculated in the 3D model, calculated against the 2D axisymmetric model, and the correction factor for the 2D axisymmetric result of each type of curvature is calculated. A database is constructed for storage, and after calculating the pressure, the correction factor in the database is used to obtain the corrected inlet-to-outlet pressure difference, and finally the calculated FFR is calculated by the formula.
本発明の上記発明を実施するための形態は本発明の原理を単に例示的に説明又は解釈するためのものであり、本発明を限定するものではないと理解されるべきである。よって、本発明の精神及び範囲を逸脱しない限り、如何なる修正、均等の差し替え、改良等もすべて本発明の保護範囲に含まれる。この他、本発明に付属の請求項は、付属の請求項の範囲及び境界、またはこれらの範囲及び境界の均等形式における全ての変更及び修正例を含むことを意図するものである。 It is to be understood that the above detailed description of the invention is merely illustrative for explaining or interpreting the principles of the invention and is not intended to be limiting of the invention. Therefore, any modification, equivalent replacement, improvement, etc., without departing from the spirit and scope of the present invention, shall fall within the protection scope of the present invention. In addition, the claims appended hereto are intended to cover all changes and modifications in the scope and boundaries of the claims appended hereto or in equivalent forms of those scopes and boundaries.
Claims (7)
S02:前記心臓画像から心臓の大動脈画像を得て、前記大動脈画像の二値化画像に対して形態学膨張を行い、心臓の全大動脈の二値画像を得て、そして画素リバースにより心臓の全大動脈相補画像を得て、前記大動脈画像において前記大動脈の中心線上点の平均グレースケールに基づき領域成長を行い、冠状動脈口を含む大動脈画像を得て、前記冠状動脈口を含む大動脈画像と前記全大動脈相補画像に基づき、冠状動脈口を含む画像を得て、冠状動脈口を含む画像に基づいて前記大動脈における前記冠状動脈口の位置を特定し、
S03:前記心筋を含む画像において前記冠状動脈口をシードポイントとし、領域成長により前記冠状動脈を抽出し、前記冠状動脈の平均グレースケールを計算し、前記冠状動脈のグレースケール分布及び前記冠状動脈の平均グレースケールを比較し、前記冠状動脈の成長方向に沿って冠状動脈ツリーを抽出し、
S04:前記冠状動脈ツリーの画像を二値化し、二値化したデータに基づいて等値面画像を三次元座標系に描き、最終的に前記冠状動脈の三次元格子画像を得て、
S05:最大充血状態における前記冠状動脈口の総流量Qtotal=心筋体積×安静状態心筋血流量×CFRを計算し、CFRは冠状動脈冠血流予備能(coronary flow reserve:CFR)であり、
S06:最大充血状態における血流速度V1を計算し、
S07:V1を冠状動脈狭窄血管の入口流速とし、冠状動脈入口から冠状動脈狭窄遠位までの圧力損失ΔP、狭窄遠位冠状動脈内平均圧Pd=Pa-ΔPを計算し、但し、Paは心臓の大動脈平均圧であり、冠血流予備量比FFR=Pd/Paを得る、
ステップを含み、
前記ステップS06は、
S61:流量体積スケーリング則及び三次元再構成の前記冠状動脈ツリーに基づき、前記冠状動脈ツリー内の任意の一本の血管内の血流量Q=Q total ×(V/V total ) 3/4 を特定し、但し、Q total は前記最大充血状態における前記冠状動脈口の総流量であり、V total は三次元再構成の前記冠状動脈ツリーの中のすべての冠状動脈の血管体積の和であり、Vは前記冠状動脈ツリー内の任意の一本の血管及びその下流血管中の血管体積の和であり、
S62:流量体積スケーリング則及び三次元再構成の前記冠状動脈ツリーに基づき、前記冠状動脈ツリー内の任意の一本の血管内の血流速度V 1 =Q/Dを特定し、但し、Dは当該血管の平均断面積である、
ことを含み、
前記ステップS07は具体的に、
血管三次元格子に対して解を求め、数値解法を用いて連続性及びナビエ-ストークス(Navier-Stokes)方程式の解を求め:
P、ρ、μはそれぞれ流速、圧力、血液密度、血液粘度であり、
入口境界条件は、最大充血状態における冠状動脈狭窄血管の入口流速V 1 であり、
三次元計算流体力学により各冠状動脈狭窄の圧力損失ΔP 1 、ΔP 2 、ΔP 3 ・・・、冠状動脈入口から冠状動脈狭窄遠位までの圧力損失ΔP=ΣΔP i (i=1、2、3・・・)、狭窄遠位冠状動脈内平均圧Pd=Pa-ΔPを計算し、但し、Paは大動脈平均である、ことを含む、
ことを特徴とする心筋血流量及びCT画像に基づく冠状動脈冠血流予備量比の計算方法。 S01: Segment a CT image including the heart, obtain a cardiac image including only the heart by morphological manipulation, histogram-analyze the cardiac image to obtain a ventricular- atrial image including only the ventricle-atrium, and combine the cardiac image with the above - mentioned obtaining an image containing the myocardium by subtracting the ventricular-atrial images, and identifying a myocardial volume based on the image containing the myocardium;
S02: Obtain a cardiac aorta image from the cardiac image, perform morphological dilation on the binarized image of the aortic image, obtain a binary image of the entire cardiac aorta, and perform pixel reversal to obtain the entire cardiac aorta image. An aorta complementary image is obtained, region growing is performed on the aorta image based on the average gray scale of points on the centerline of the aorta , an aorta image including the coronary ostium is obtained, and the aorta image including the coronary ostium and the total aorta image are obtained. obtaining an image including the coronary ostium based on the aorta complementary image, and identifying the location of the coronary ostium in the aorta based on the image including the coronary ostium;
S03: In the image including the myocardium, the ostium of the coronary artery is used as a seed point, the coronary artery is extracted by region growing, the average grayscale of the coronary artery is calculated, and the grayscale distribution of the coronary artery and the coronary artery are calculated . extracting the coronary artery tree along the growth direction of said coronary arteries by comparing the average grayscale of
S04: binarize the image of the coronary artery tree , draw an isosurface image in a three-dimensional coordinate system based on the binarized data , and finally obtain a three-dimensional grid image of the coronary artery,
S05: Calculate the total flow Q total of the coronary artery ostia in the state of maximum hyperemia = myocardial volume × resting myocardial blood flow × CFR, where CFR is the coronary flow reserve (CFR);
S06: Calculate the blood flow velocity V1 in the state of maximum hyperemia,
S07: Calculate the pressure loss ΔP from the coronary entrance to the distal coronary artery stenosis and the mean intracoronary artery distal stenosis pressure P d =P a −ΔP, where V 1 is the inlet flow velocity of the coronary artery stenosis, provided that: P a is the mean aortic pressure of the heart , giving the coronary flow reserve ratio FFR=P d /P a
including steps
The step S06 is
S61: Based on the flow-volume scaling law and the three-dimensional reconstruction of the coronary artery tree, the blood flow in any one vessel in the coronary artery tree Q = Q total × ( V / V total ) 3/4 wherein Q total is the total flow of the coronary ostia at the maximum hyperemic state, V total is the sum of vessel volumes of all coronary arteries in the coronary tree of the three-dimensional reconstruction; V is the sum of vessel volumes in any one vessel in the coronary artery tree and its downstream vessels;
S62: Determine the blood flow velocity V 1 =Q/D in any one vessel in the coronary artery tree based on the flow-volume scaling law and the three-dimensional reconstruction of the coronary artery tree, where D is is the average cross-sectional area of the blood vessel,
including
Specifically, the step S07 is
Solve for the vessel 3D grid and solve the continuity and Navier-Stokes equations using numerical methods:
P, ρ, μ are flow velocity, pressure, blood density, blood viscosity, respectively,
The inlet boundary condition is the inlet flow velocity V1 of the coronary artery stenosis at maximum hyperemia ,
By three-dimensional computational fluid dynamics, the pressure losses ΔP 1 , ΔP 2 , ΔP 3 , . ), calculating the mean pressure in the stenotic distal coronary artery Pd = Pa - ΔP, where Pa is the aortic mean,
A method for calculating a coronary flow reserve ratio based on a myocardial blood flow and a CT image, characterized by:
前記冠状動脈画像V1中のボクセルをトラバーサルし、もしボクセル画素が0に等しい場合、当該画素値は変わらず、もし0に等しくない場合、画素値を1とし、これらの画素値は一つの新しいデータV2となることを含む、
ことを特徴とする請求項1に記載の心筋血流量及びCT画像に基づく冠状動脈冠血流予備量比の計算方法。 Coronary artery image binarization in step S04 includes:
Traversing the voxels in the coronary artery image V1, if a voxel pixel is equal to 0, the pixel value remains unchanged, if not equal to 0, the pixel value is 1, and these pixel values are a new data. including becoming V2,
2. The method for calculating a coronary artery coronary flow reserve ratio based on a myocardial blood flow and a CT image according to claim 1.
ことを特徴とする請求項1に記載の心筋血流量及びCT画像に基づく冠状動脈冠血流予備量比の計算方法。 Resting-state myocardial blood is measured by myocardial contrast echocardiography (MCE), single photon emission tomography (SPECT), positron emission tomography (PET), cardiac magnetic resonance imaging (MRI), or CT perfusion in step S05. determining flow rate and coronary flow reserve (CFR);
2. The method for calculating a coronary artery coronary flow reserve ratio based on a myocardial blood flow and a CT image according to claim 1.
CT再構成の前記冠状動脈の三次元格子画像に基づき、狭窄のある血管を真っすぐに引き伸ばし、二次元軸対称モデルを構築し、二次元格子を分割し、数値解法を用いて連続性及びナビエ-ストークス方程式の解を求め:
入口境界条件は、最大充血状態における冠状動脈狭窄血管の入口流速V1であり、
二次元流体力学により各冠状動脈狭窄の圧力損失ΔP1、ΔP2、ΔP3・・・、冠状動脈入口から冠状動脈狭窄遠位までの圧力損失ΔP=ΣΔPi(i=1、2、3・・・)、狭窄遠位冠状動脈内平均圧Pd=Pa-ΔPを計算する、但し、Paは大動脈平均圧である、ことを含む、ことを特徴とする請求項1に記載の心筋血流量及びCT画像に基づく冠状動脈冠血流予備量比の計算方法。 The step S07 is
Based on the CT-reconstructed three-dimensional grid image of the coronary artery , the stenosed vessel is straightened, a two-dimensional axisymmetric model is constructed, the two-dimensional grid is divided, and continuity and navigator analysis is performed using numerical methods. Find the solution of the Stokes equation:
The inlet boundary condition is the inlet flow velocity V1 of the coronary artery stenosis at maximum hyperemia,
Pressure loss ΔP 1 , ΔP 2 , ΔP 3 , . . . ), calculating the stenotic distal coronary mean pressure P d =P a −ΔP, where P a is the aortic mean pressure. Method for calculating coronary artery flow reserve ratio based on blood flow and CT images.
前記冠状動脈の異なるタイプの弯曲に対して、前記冠状動脈の三次元格子画像で冠状動脈入口から冠状動脈狭窄遠位までの圧力損失を計算し、前記二次元軸対称モデルに照らして計算し、各タイプの弯曲の二次元軸対称結果に対する修正係数を記憶するためのデータベースを構築し、
圧力損失を得た後、前記データベース中の修正係数に照らし、修正後の冠状動脈入口から冠状動脈狭窄遠位までの圧力損失を得て、その後前記FFRを計算する、
ことを含む、ことを特徴とする請求項6に記載の心筋血流量及びCT画像に基づく冠状動脈冠血流予備量比の計算方法。 The step S07 further includes
calculating the pressure drop from the coronary ostium to the distal coronary artery stenosis on a three-dimensional grid image of the coronary artery for different types of curvature of the coronary artery and in light of the two-dimensional axisymmetric model; constructing a database for storing correction factors for the two-dimensional axisymmetric results of each type of curvature;
After obtaining the pressure drop , obtain the corrected pressure drop from the coronary ostium to the distal coronary artery stenosis in light of the correction factors in the database, and then calculate the FFR.
7. The method for calculating the coronary coronary flow reserve ratio based on myocardial blood flow and CT images according to claim 6 , characterized by comprising:
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